Deep-learning Transfer Learning models of NTUA-SLP team submitted at the IEST of WASSA 2018 at EMNLP 2018.

LSTM and QRNN Language Model Toolkit for PyTorch 1.2.0!

PyTorch implementation of Variational LSTM and Monte Carlo dropout.

Source code for the ACL 2019 paper "Attention-based Conditioning Methods for External Knowledge Integration"

Code for evaluating uncertainty estimation methods for Transformer-based architectures in natural language understanding tasks.

Code for the EMNLP 2021 Paper "Active Learning by Acquiring Contrastive Examples" & the ACL 2022 Paper "On the Importance of Effectively Adapting Pretrained Language Models for Active Learning"

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.